Engine control system using a cascaded neural network

Data processing: artificial intelligence – Neural network – Structure

Reexamination Certificate

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Reexamination Certificate

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11340515

ABSTRACT:
A method, system and machine-readable storage medium for monitoring an engine using a cascaded neural network that includes a plurality of neural networks is disclosed. In operation, the method, system and machine-readable storage medium store data corresponding to the cascaded neural network. Signals generated by a plurality of engine sensors are then inputted into the cascaded neural network. Next, a second neural network is updated at a first rate, with an output of a first neural network, wherein the output is based on the inputted signals. In response, the second neural network outputs at a second rate, at least one engine control signal, wherein the second rate is faster than the first rate.

REFERENCES:
patent: 4193115 (1980-03-01), Albus
patent: 5377112 (1994-12-01), Brown, Jr. et al.
patent: 5418864 (1995-05-01), Murdock et al.
patent: 5532938 (1996-07-01), Kondo et al.
patent: 5570282 (1996-10-01), Hansen et al.
patent: 5634063 (1997-05-01), Ahn et al.
patent: 5682317 (1997-10-01), Keeler et al.
patent: 5796922 (1998-08-01), Smith
patent: 5822741 (1998-10-01), Fischthal
patent: 5825936 (1998-10-01), Clarke et al.
patent: 5832421 (1998-11-01), Santoso et al.
patent: 5857321 (1999-01-01), Rajamani et al.
patent: 5877954 (1999-03-01), Klimasauskas et al.
patent: 5971747 (1999-10-01), Lemelson et al.
patent: 6092017 (2000-07-01), Ishida et al.
patent: 6098012 (2000-08-01), Stander et al.
patent: 6108648 (2000-08-01), Lakshmi et al.
patent: 6216083 (2001-04-01), Ulyanov et al.
patent: 6236908 (2001-05-01), Cheng et al.
patent: 6240343 (2001-05-01), Sarangapani et al.
patent: 6272241 (2001-08-01), Tattersall
patent: 6278962 (2001-08-01), Klimasauskas et al.
patent: 6278986 (2001-08-01), Kamihira et al.
patent: 6349293 (2002-02-01), Yamaguchi
patent: 6401457 (2002-06-01), Wang et al.
patent: 6440067 (2002-08-01), DeLuca et al.
patent: 6466859 (2002-10-01), Fujime
patent: 6490571 (2002-12-01), Cooper
patent: 6574613 (2003-06-01), Moreno-Barragan
patent: 6616057 (2003-09-01), Kelly et al.
patent: 6792412 (2004-09-01), Sullivan et al.
patent: 6826550 (2004-11-01), Brown et al.
patent: 7062333 (2006-06-01), Mizutani
patent: 2004/0122785 (2004-06-01), Brown et al.
Li et al, “A Cascaded Neural Network and Its Application to Modeling Power Plant Pollutant Emission”, IEEE Proceeedings of the 3rd World Congress on Intelligent Control and Automation, Jun.-Jul. 2000.
Comoglio et al, “Using a Cerebellar Model Arithmetic Computer (CMAC) Neural Network to Control an Autonomous Underwater Vehicle”, IEEE IJCNN, 1992.
Geng et al, “Neural Network Solution for the Forward Kinematics Problem of a Stewart Platform”, IEEE International Conference an Robotics and Automation, Apr. 1999.
Huang et al, “Cascade-CMAC Neural Network Applications on the Color Scanner to Printer Calibration”, IEEE IJCNN, Jun. 1997.
Uno et al, “Repetitively Structured Cascade Neural Network Model Which Generates an Optimal Arm Trajectory,” IEEE Proceedings of the 28thConference on Decision and Control, Tampa, FL (Dec. 1989), pp. 1750 and 1751.
Cichocki, A., et al, “Dual Cascade Networks for Blind Signal Extraction,” 1997 IEEE (Aug. 1997), pp. 2135-2140.

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